• Title/Summary/Keyword: Panel Data Regression

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The Effects of Trading-Hour Regulations on Large Stores in Korea

  • Kim, Woohyoung;Lee, Hahn-Shik
    • Journal of Distribution Science
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    • v.15 no.8
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    • pp.5-14
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    • 2017
  • Purpose - This study empirically analyses the sale changes in large retail stores directly resulting from increased controls on those stores. More specifically, we discuss the economic impacts on Korean regulations that restrict trading hours and mandate statutory store closure 'holidays' twice per month. Research design, data and methodology - we attempt to empirically analyse the economic effects of trading hours regulations through quantitative analysis of the sales revenue data of large retail stores. We introduce the data and methods of empirical analysis used to analyse the economic effects of trading-hour regulations on large retail stores. We use a panel regression to analyse the sales losses of large retail stores caused by the new constraints on business hours. Results - The results of this study show that the sales of large retail stores fell by the average of 3.4% per month during the regulation periods. However, regulations affecting large retail stores have various economic impacts, including variations in sales, changes in consumption patterns, and influences on consumer welfare and national economy. Conclusions - Such changes may also be captured by other metrics: accordingly, further researches are needed to measure the impact of regulations on economic indicators such as employment and GDP.

Competition of Islamic Bank in Indonesia

  • Humairoh, Syafaqatul;Usman, Hardius
    • Journal of Distribution Science
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    • v.14 no.6
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    • pp.39-44
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    • 2016
  • Purpose - This paper aims to study the competition that occurs in the Islamic Banking industry and to analyze the variables that affect the total revenue of Islamic Banking in Indonesia. Research Design, Data and Methodology - This study observed 10Islamic banks for the period 2010-2013. The annual data are taken from Direktori Perbankan Indonesia, published by Bank Indonesia, and annual report of the observed banks. In analyzing data, Panzar Rosse Approach was applied to analyze the type of Islamic Bank Market and Panel Regression Model for the estimated co-efficients has been used in the Panzar Rosse Approach. Results - Estimation model shows that all the banking cost elements such as the price of capital, unit price of labor, and unit prices of funds have significant positive correlation to Revenue as a dependent variable. The estimated value of H-statistic for the period 2010-2013 is 0.69. It can be interpreted that Islamic banking market in Indonesia shows monopolistic competition. Price of capital and funds has statistically significant effect on Bank's Revenue. Conclusions - The study revealed that the Islamic banking market competition in Indonesia is monopolistic and the major contribution to the H-statistic comes from mainly price of funds.

Factors Affecting Capital Structure of Listed Construction Companies on Hanoi Stock Exchange

  • NGUYEN, Nguyet Minh;TRAN, Kien Trung
    • The Journal of Asian Finance, Economics and Business
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    • v.7 no.11
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    • pp.689-698
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    • 2020
  • The aim of this article is to determine the influence of factors on the capital structure of construction companies listed on the Hanoi Stock Exchange. The data of the article were collected and calculated from the financial statements of 54 construction companies listed on Hanoi Stock Exchange from 2012 to 2019. With the application of E-view software in quantitative analysis to build panel data regression model (panel data), the article has built a regression model to determine the relationship of intrinsic factors affecting the capital structure of construction companies listed on Hanoi Stock Exchange. In the study, dependent variable is capital structure, determined by the debt-to-equity ratio. Profitability, coefficient of solvency, size, loan interest rate, structure of tangible assets, and growth are independent variables. The results showed that the two factors of growth and firm size positively affect the capital structure, the profitability factor has the opposite effect on capital structure. Factors of short-term debt solvency, average loan interest rate and tangible asset structure have no correlation with capital structure. The findings of this article are useful for business administrators, helping business managers make the right financial decisions to make capital structure decisions in their own conditions.

Macroeconomic and Firm-specific Factors Influencing Non-Performing Loans in Bangladesh: A Panel Data Regression Approach

  • AMIN, Md. Iftekharul;AHSAN, Aumit;Al MUKTADIR, Mahmud;AZAD, Muntasir;REZANUR, Razib Hasan Bin
    • The Journal of Asian Finance, Economics and Business
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    • v.8 no.12
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    • pp.95-105
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    • 2021
  • A prerequisite of a sound financial system is effective channeling of financial resources to efficient users; hence maximizing economic and societal welfare. To that end, the prevalence of bad loans in banks in emerging economies is a major policy concern. In an attempt to add to the growing body of literature explaining the interrelationship between macroeconomic and firm-specific factors, and non-performing loans (NPL), this paper examines data from 24 scheduled commercial banks in Bangladesh from 2008 to 2019. Macroeconomic factors as well as firm-specific factors related to profitability, capital strength, and efficiency are considered. Panel data regression analysis is performed to estimate pooled OLS, fixed effects, and random effects models. Following the necessary testing, it was found that the fixed effects model with robust standard error is appropriate. Results show that return on assets and inflation have a negative influence on NPL, but GDP growth has a favorable impact. The paper concludes by asserting that the evidence supports similar findings from studies both in Bangladesh and elsewhere and it is noted that a combination of these macroeconomic and firm-specific factors explains only a small portion of the total variation in NPL.

Household, personal, and financial determinants of surrender in Korean health insurance

  • Shim, Hyunoo;Min, Jung Yeun;Choi, Yang Ho
    • Communications for Statistical Applications and Methods
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    • v.28 no.5
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    • pp.447-462
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    • 2021
  • In insurance, the surrender rate is an important variable that threatens the sustainability of insurers and determines the profitability of the contract. Unlike other actuarial assumptions that determine the cash flow of an insurance contract, however, it is characterized by endogenous variables such as people's economic, social, and subjective decisions. Therefore, a microscopic approach is required to identify and analyze the factors that determine the lapse rate. Specifically, micro-level characteristics including the individual, demographic, microeconomic, and household characteristics of policyholders are necessary for the analysis. In this study, we select panel survey data of Korean Retirement Income Study (KReIS) with many diverse dimensions to determine which variables have a decisive effect on the lapse and apply the lasso regularized regression model to analyze it empirically. As the data contain many missing values, they are imputed using the random forest method. Among the household variables, we find that the non-existence of old dependents, the existence of young dependents, and employed family members increase the surrender rate. Among the individual variables, divorce, non-urban residential areas, apartment type of housing, non-ownership of homes, and bad relationship with siblings increase the lapse rate. Finally, among the financial variables, low income, low expenditure, the existence of children that incur child care expenditure, not expecting to bequest from spouse, not holding public health insurance, and expecting to benefit from a retirement pension increase the lapse rate. Some of these findings are consistent with those in the literature.

Influence of parenting role sharing, parenting stress, and happiness on warm parenting behavior in mothers of children aged 6 years: an analysis using data from the seventh panel study on Korean children

  • Bang, Kyung-Sook;Jang, Sang-Youn
    • Child Health Nursing Research
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    • v.28 no.1
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    • pp.82-90
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    • 2022
  • Purpose: The aim of this study was to examine the relationships among parenting role sharing, parenting stress, happiness, and parenting behavior of mothers with 6-year-old children. Methods: This study used data from the seventh Panel Study of Korean Children, which began collecting longitudinal data on a sample of newborn households nationwide in 2008 and will continue yearly until 2027. The participants were 1,560 mothers of children aged 6 years. We conducted statistical analyses using descriptive statistics, the t-test, analysis of variance, Pearson correlation coefficients, and stepwise multiple regression. Results: The mean age of the mothers was 36.8±3.7 years. The mothers' perceived parenting role sharing (r=.07, p=.007), parenting stress (r=-.54, p<.001), and happiness (r=.38, p<.001) were significantly correlated with warm parenting behavior. Stepwise multiple regression analysis revealed that parenting stress (β=-.47, p<.001), happiness (β=.15, p<.001), and parenting role sharing (β=.11, p<.001) were significant predictors for warm parenting behavior by mothers. Conclusion: It is essential to reduce mothers' stress and increase their positive emotions (happiness). Fathers should actively share parenting roles in raising children to enhance mothers' warm parenting behavior.

Longitudinal Study on the Equity of National Health Insurance Contribution of the self-employed (건강보험 지역가입자의 보험료 부담 형평성 종단분석)

  • Rhee, Okjin;Moon, Yongpil;Park, Hyunshik
    • Korean Journal of Social Welfare Studies
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    • v.47 no.4
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    • pp.309-332
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    • 2016
  • This research attempts to calculate the vertical equity of National Health Insurance Contribution of locally provided policy holders by abilities to pay. Also, this longitudinal study examined the influence of abilities to pay and demographic characteristics on the health insurance premium. Using data from the Korea Welfare Panel Study, this study followed the self-employed households who continued to participate in the survey from 2011 to 2015. Kakwani's index of progressivity was measured as a measure of vertical equity and panel regression analysis was conducted by STATA program. The results of this research are as follows. First, from 2011 to 2015, the values of kakwani's index were negative according to composite income, which meant some levels of regressiveness of contribution. Secondly, panel regression analysis showed that the lowest household of composite income had a significantly negative effect on premiums, which also meant regressiveness. Based on the results, the author suggested political discussions on reorganizing the system of imposing the National Health Insurance contribution.

Analysis of Determinants of Civilian City Gas Demand Considering Spatial Correlation (공간적 상관성을 고려한 민수용 도시가스 수요결정 요인 분석)

  • Eunbi Park;DooHwan Won
    • Environmental and Resource Economics Review
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    • v.33 no.1
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    • pp.59-86
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    • 2024
  • Recently, research on city gas demand is increasing by reflecting the characteristics of each region. The similarity of the social structure of the adjacent region and the density of the supply infrastructure induce spatial correlation with the clustering that has a microscopic relationship between regions. Accordingly, as a result of analyzing the spatial correlation after dividing the demand for city gas for civilian use into a total of 54 regions based on the jurisdiction of 34 city gas companies, it was confirmed that there was a positive spatial correlation from a global and local perspective. In this study, the demand for city gas for civilian use for 54 regions from January 2014 to December 2022 was composed of panel data, and the spatial panel regression analysis and the general panel regression analysis were compared, and it was found that the spatial error model (SEM) was the most suitable model. This presents policy and practical implications by confirming that the demand for city gas for civilian use in one region has a significant relationship with the adjacent region.

Onion yield estimation using spatial panel regression model (공간 패널 회귀모형을 이용한 양파 생산량 추정)

  • Choi, Sungchun;Baek, Jangsun
    • The Korean Journal of Applied Statistics
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    • v.29 no.5
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    • pp.873-885
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    • 2016
  • Onions are grown in a few specific regions of Korea that depend on the climate and the regional characteristic of the production area. Therefore, when onion yields are to be estimated, it is reasonable to use a statistical model in which both the climate and the region are considered simultaneously. In this paper, using a spatial panel regression model, we predicted onion yields with the different weather conditions of the regions. We used the spatial auto regressive (SAR) model that reflects the spatial lag, and panel data of several climate variables for 13 main onion production areas from 2006 to 2015. The spatial weight matrix was considered for the model by the threshold value method and the nearest neighbor method, respectively. Autocorrelation was detected to be significant for the best fitted model using the nearest neighbor method. The random effects model was chosen by the Hausman test, and the significant climate variables of the model were the cumulative duration time of sunshine (January), the average relative humidity (April), the average minimum temperature (June), and the cumulative precipitation (November).

Design-based Properties of Least Square Estimators in Panel Regression Model (패널회귀모형에서 회귀계수 추정량의 설계기반 성질)

  • Kim, Kyu-Seong
    • Survey Research
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    • v.12 no.3
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    • pp.49-62
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    • 2011
  • In this paper we investigate design-based properties of both the ordinary least square estimator and the weighted least square estimator for regression coefficients in panel regression model. We derive formulas of approximate bias, variance and mean square error for the ordinary least square estimator and approximate variance for the weighted least square estimator after linearization of least square estimators. Also we compare their magnitudes each other numerically through a simulation study. We consider a three years data of Korean Welfare Panel Study as a finite population and take household income as a dependent variable and choose 7 exploratory variables related household as independent variables in panel regression model. Then we calculate approximate bias, variance, mean square error for the ordinary least square estimator and approximate variance for the weighted least square estimator based on several sample sizes from 50 to 1,000 by 50. Through the simulation study we found some tendencies as follows. First, the mean square error of the ordinary least square estimator is getting larger than the variance of the weighted least square estimator as sample sizes increase. Next, the magnitude of mean square error of the ordinary least square estimator is depending on the magnitude of the bias of the estimator, which is large when the bias is large. Finally, with regard to approximate variance, variances of the ordinary least square estimator are smaller than those of the weighted least square estimator in many cases in the simulation.

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